Research & Publications

Lab faculty, staff and students engage in a range of advanced research and development
activities. The vast majority of the Lab’s work involves the development of novel robotic control
strategies and the verification of these strategies through both simulation and experiments.
Student work results in university documents such as capstone reports, theses, and dissertations.
In many cases, portions of our work is published and presented in public venues. Below is a
summary of some of the Lab’s primary areas of work.

Cluster Space Formation Control of Multirobot Systems: The Lab is the home of the cluster space multirobot formation control technique. This is a full degree-of-freedom operational space control strategy with formalized mathematics, provably stable behavior, and applicability to a wide range of land/sea/air systems. The technique envisions a group of robots as a virtual articulating mechanism and allows a single pilot or a higher-level automated controller to specify desired motions and the geometric characteristics of the group in a simple, intuitive manner. Key publications include:

C. Kitts and I. Mas, “Cluster Space Specification and Control of Multi-Robot Systems,” IEEE/ASME Trans. On Mechatronics, v14 n2, pp. 207-218, 2009.

I. Mas and C. Kitts, “Dynamic Control of Mobile Multirobot Systems,” IEEE Access, v2, pp. 558-570, 2014.

Swarm Control of Multirobot Systems: The Lab has also explored the use of “swarm”
approaches to multirobot formation control. Such techniques generally do NOT fully prescribe
all degrees of freedom for the system and generally use de-centralized controller laws with
potentially limited state information. Key publications include:

S. Hart and C. Kitts, “Unifying Control Architecture for Reactive Particle Swarms,” IEEE/ASME
Transactions on Mechatronics, v28 n2, pp. 873-883, 2022.

S. Hart, J. Kamenetsky, and C. Kitts, “Dynaic Elliptical Shaping Control for Swarm Robots,”
IEEE Access, v11, pp. 17454-17470, 2023.

Adaptive navigation of environmental scalar fields: The Lab is a leader in multirobot techniques to adaptively locate and move along points of interest in an environmental scalar field (e.g., a region over which a parameter varies, such as temperature, radiation level, or the concentration of a pollutant). In particular, we have developed a hierarchical control technique based on our cluster space formation controller that allows us to use multirobot clusters to find these interesting points without exhaustively mapping the entire region. Capabilities of interest include locating the max/min points in a field, moving along contours, moving down/up ridge/trench formations, locating saddle points, and moving along frontlines. These capabilities are fundamental for applications such as disaster response, environmental monitoring/characterization, exploration and security.

T. Adamek, C. Kitts, and I. Mas, “Gradient-based Cluster Space Navigation for Autonomous Surface Vessels,” IEEE/ASME Trans. on Mechatronics, vol 20 no 2, pp. 506-518, 2014.

C. Kitts, R. McDonald, M. Neumann, “Adaptive Navigation Control Primitives for Multirobot Clusters,” IEEE Access, vol 6, pp. 17625-17642, 2018.

R. Lee, C. Kitts, M. Neumann, and R. McDonald, “Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields,” IEEE Access, v9, pp. 122,626-122,654, 2021.

Additional Applications of our Work in Cluster Space Multirobot Control: In addition to using our cluster space control technique to enable adaptive navigation capabilities, we have applied it for a wide range of other applications that benefit from distributed functionality.  These applications include escorting and guarding other objects, manipulating/transporting large objects, and optimally tracking targets.

I. Mas, S. Li, J. Acain, and C. Kitts, "Entrapment/Escorting and Patrolling Missions in Multi-Robot Cluster Space," 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, 2009, pp. 5855-5861, 2009.

P. Mahacek, C. Kitts, and I. Mas, "Dynamic Guarding of Marine Assets Through Cluster Control of ASV Fleets," IEEE/ASME Trans. on Mechatronics, vol 17 no 1, pp. 65-75, 2012.

M. Neumann and C. Kitts, "A Hybrid Multirobot Control Architecture for Object Transport," IEEE/ASME Trans. on Mechatronics, vol 21 no 6, pp. 2983-2988, 2016.

J. Cashbaugh and C. Kitts, "Vision-Based Object Tracking Using an Optimally Positioned Cluster," IEEE Systems Journal, vol 12 no 2, pp. 1423-1434, 2018.

Human-Cobot Object Co-Manipulation: This is an evolving research area in the lab. It involves the development of reactive “cobot” approaches to object manipulation in which one or more robots provide the “heavy lifting” for an object while a human operator guides the object along a desired path. We have explored cases in which the operator physically interacts with the object (Ambauen, MS Thesis, 2011) as well as approaches in which the operator provides two-handed gestures referenced to the object in order to command object translations and rotations (Nazir, MS Thesis, 2024). These are “no programming” approaches to employing robotic systems (manipulators, mobile robots, and mobile manipulators) for transporting and manipulating physical objects. We are developing multiple publications on this work and will post them once published.

Causal/Model-based AI for anomaly management: We have developed a comprehensive model-based conceptual framework for different types of anomalies that occur in functional engineering systems, to include a unified framework for their detection, diagnosis and resolution. We have been applying this to the operational control of the robotic systems we build and deploy. An initial article on this work is listed below, but there have been numerous additional conference papers on our work applying anomaly management techniques to the NASA spacecraft that we operate.

C. Kitts, “Managed Space System Anomalies Using First Principles Reasoning,” IEEE Robotics & Automation Magazine, vol 13 no 4, pp. 39-50, 2006.